Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Superior-Trade/superior-skills --skill backtestinggit clone --depth 1 https://github.com/Superior-Trade/superior-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/superior-trade/superior-skills/backtesting)<a href="https://agentmods.dev/skills/superior-trade/superior-skills/backtesting"><img src="https://agentmods.dev/badge/skills/superior-trade/superior-skills/backtesting.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 22 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 99 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 104 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.02611 |
| Opus 5 | $0.00036 | $0.01306 |
| Sonnet 5 | $0.00015 | $0.00522 |
| Haiku 4.5 | $0.00007 | $0.00261 |
Grade A, and why
backtesting scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Backtesting Best Practices
Read ../../references/unified-runtime.md
for the shared API lifecycle. Submit every run with POST /runtime/backtests;
creation queues it, so there is no separate start request. Use the framework and
venue fields defined by GET /openapi.json and the relevant venue skill. This
page is about the judgment calls — picking a window that means something,
telling signal from noise in the result, and knowing when to give up vs. iterate.
The trade-count bar (sample size first)
Trade count is the single most important number on a result page. Look at it before PnL, before Sharpe, before win rate.
| Trade count | Verdict |
|---|---|
| < 30 | Coincidence, not a strategy. Don't promise anything; widen entries or extend window. |
| 30-50 | Marginal. Sharpe is noisy. Treat results as directional, not numeric. |
| 50-200 | Useful. Sharpe / profit factor start to mean something. |
| 200+ | Statistical confidence. Now you can compare variants on micro-differences. |
Watch for the trap: backtests with 5-10 trades and a 100% win rate. They look like world-beaters and almost always disintegrate live. The strategy is too selective — every signal is a coin flip you've cherry-picked, not a repeatable edge. Widen the entry threshold, lengthen the window, or accept that there's no statistical signal here.
Pick a backtest window that means something
A great backtest over the wrong window is a great fiction.
The window should answer: "if I had deployed this strategy on day one of this window, what would have happened?" — not "what's the prettiest curve I can fit?"
Cover at least one regime change
Pure bull, pure bear, sideways chop — your window should include at least two of the three. A 90-day backtest in a one-direction market is a 90-day cherry-pick. A momentum strategy that prints +50% over a +60% trending window has told you nothing about itself; it's just measured beta.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago Changed · +5 lines a96b58dcab47
- 8d ago First seen · 170 lines · 73 tokens per session scan A 71db4c42a05b
backtesting is a skill published in the GitHub repository Superior-Trade/superior-skills (208 stars, last pushed 4d ago), licensed MIT. It adds 73 tokens to every session and 2,611 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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